1. Joint Modeling
1.1 Trace plots for convergence check
The current MCMC setting is:
- 4000000 iteration;
- 3000000 burn-in;
- 1000 thinning.
1.2 Gelman and Rubin’s convergence check
## Potential scale reduction factors:
##
## Point est. Upper C.I.
## HDevsum 1 1.00
## LDevsum 1 1.00
## dh0 1 1.00
## dl0 1 1.00
## dl1 1 1.00
## dl2 1 1.00
## dl3 1 1.01
##
## Multivariate psrf
##
## 1
1.3 ACF Plots
Here we plotted ACF plots for the following variables:
- Total deviance;
- Variables that didn’t pass the convergence check.
1.4 WAIC results
| LevelH | LevelL | |
|---|---|---|
| DIC | 1355.01341 | 24459.764 |
| DIC3 | 1238.38872 | 21023.016 |
| PWAIC | 79.76607 | 1268.875 |
| WAIC | 1295.56531 | 21594.056 |
2. Separate Modeling of High-Level
2.1 Trace plots for convergence check
The current MCMC setting is:
- 4000000 iteration;
- 3000000 burn-in;
- 1000 thinning.
2.2 Gelman and Rubin’s convergence check
## Potential scale reduction factors:
##
## Point est. Upper C.I.
## HDevsum 1.00 1.00
## dh0 1.01 1.03
##
## Multivariate psrf
##
## 1.01
2.3 ACF Plots
Here we plotted ACF plots for the following variables:
- Total deviance;
- Variables that didn’t pass the convergence check.
2.4 WAIC results
| H0 | |
|---|---|
| DIC | 1399.72005 |
| DIC3 | 1261.85042 |
| PWAIC | 95.81052 |
| WAIC | 1335.33404 |
3. Separate Modeling for Low-level
3.1 Trace plots for convergence check
The current MCMC setting is:
- 4000000 iteration;
- 3000000 burn-in;
- 1000 thinning.
3.2 Gelman and Rubin’s convergence check
## Potential scale reduction factors:
##
## Point est. Upper C.I.
## LDevsum 1.00 1.02
## dl0 1.19 1.66
## dl1 1.02 1.08
## dl2 1.18 1.64
## dl3 1.00 1.02
##
## Multivariate psrf
##
## 1.12
3.3 ACF Plots
Here we plotted ACF plots for the following variables:
- Total deviance;
- Variables that didn’t pass the convergence check.
3.4 WAIC results
| L4 | |
|---|---|
| DIC | 24355.410 |
| DIC3 | 20959.399 |
| PWAIC | 1174.934 |
| WAIC | 21466.667 |